20 Top Generative AI Companies Leading In 2024

Generative AI companies are popping up everywhere and quickly. They range from established companies adding generative AI to their software products to new generative AI startups.
As generative AI rapidly develops, it can be difficult to distinguish between the leading generative AI companies and the hundreds of others that are beginning to tap into this AI technology and explore its vast potential.
To assist, this guide covers the top 20 generative AI companies, detailing their products and potential use cases. We’ll also provide analysis into how and why these generative AI companies are growing in popularity so quickly.

TABLE OF CONTENTS
ToggleTop Generative AI Companies ComparedOpenAIMicrosoftAlphabet (Google)Amazon (AWS)NVIDIAAnthropicCohereGleanJasperHugging FaceInflection AIAdobeIBMC3.aiMetaDatabricksStability AISynthesiaGrammarlyMOSTLY AIKey Features of Generative AI CompaniesHow to Choose the Best Generative AI Companies for Your BusinessFrequently Asked Questions (FAQs)Bottom Line: Reviewing the Top Generative AI Companies





Top Generative AI Companies Compared
Each of these generative AI companies offers unique product portfolios and solutions that set them apart from their competition; therefore, instead of comparing them across the same core criteria, we’ll instead take a look at their key business stats, products, and market value.
In this table, we’ve covered the 10 best generative AI companies, while the rest of this guide will look at these organizations plus 10 additional generative AI leaders.

Headquarters
Founded
Company Size
Key Products
Market Cap (as of March 2024)

OpenAI
San Francisco, CA, USA
2015
200-500 employees
GPT-4, ChatGPT, DALL-E 3, Sora
Private company valued at $80 billion+

Microsoft
Redmond, WA, USA
1975
220,000+ employees
Microsoft Copilot, Copilot for Microsoft 365, Microsoft Copilot Studio, Microsoft Copilot in Bing
$3.01 trillion

Alphabet (Google)
Mountain View, CA, USA
1998
180,000+ employees
Gemini, Vertex AI, Gemini for Google Workspace
$1.72 trillion

Amazon (AWS)
Seattle, WA, USA
1994
1.5 million+ employees
Amazon Bedrock, Amazon Q, Amazon CodeWhisperer, Amazon SageMaker
$1.79 trillion

NVIDIA
Santa Clara, CA, USA
1993
29,000+ employees
NVIDIA AI, NVIDIA NeMo, NVIDIA BioNeMo, NVIDIA Picasso, various chips and GPUs
$2.14 trillion

Anthropic
San Francisco, CA, USA
2021
50-300 employees
Claude 3, Claude API
Private company valued at $15 billion

Cohere
Toronto, ON, Canada
2019
50-300 employees
Command, Embed, Chat, Generate, Semantic Search
Private company valued at $2.2 billion

Glean
Palo Alto, CA, USA
2019
200-500 employees
Glean, Glean Chat, Glean Assistant
Private company valued at $2.2 billion

Jasper
Austin, TX, USA
2020
50-200 employees
Jasper, Jasper API, Jasper AI Copilot
Private company valued at $1.2 billion

Hugging Face
Brooklyn, NY, USA
2016
100-300 employees
BLOOM, AutoTrain, Inference Endpoints
Private company valued at $4.5 billion

OpenAI
Best overall

Headquarters: San Francisco, CA, USA
Founded: 2015
Company Size: 200-500 employees
Key Products: GPT-4, ChatGPT, DALL-E 3, Sora
Market Cap: Private company valued at $80 billion+

Since OpenAI first publicly released ChatGPT in late 2022, it has completely shaped the generative AI landscape with its innovations across different types of content generation and AI research. OpenAI is the most successful dedicated generative AI company to date, worth an estimated $80 billion+ and backed by major tech companies like Microsoft.
Beyond its flagship content generation solution, ChatGPT, and image generation solution, DALL-E, OpenAI also offers its API and different generative AI models to support companies in their own AI development efforts. GPT-4, chat models, instruct models, fine-tuning models, audio models, image models, and embedding models can all be customized for a usage fee to meet individual business needs.
Most recently, OpenAI has also announced Sora, a generative AI video solution, and the GPT Store, which will make it easier for users to select custom-built versions of ChatGPT that align with their specific business use cases and requirements.

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Pros and cons

Pros
Cons

Well-funded and innovative company.
No real-time information informing results in free tool.

General availability of APIs and fine-tuning models.
Usage-based model access can become expensive.

Pricing
OpenAI offers a wide range of products with different subscription and usage-based pricing options. We’ve covered a few of its top products below, but more pricing information can be found here.

ChatGPT: $0 for Free, $20 per user per month for Plus, $25-$30 per user per month for Team, and custom pricing for Enterprise plan.
DALL-E 3 model: Between $0.40 and $0.10 per image, depending on selected quality and resolution.
GPT-4 model: Between $30 and $60 per 1 million input tokens and between $60 and $120 per 1 million output tokens.

Features

ChatGPT chatbot with multimodal outputs based on GPT-3.5 or GPT-4, depending on selected plan.
DALL-E family of tools for high-quality image generation.
APIs, base, embedding, and fine-tuning models.
Sora for text-to-video content generation.
GPT Store for ChatGPT customizations.

To see a list of the leading generative AI apps, read our guide: Top 20 Generative AI Tools and Apps 2024.

Microsoft
Best enterprise generative AI partner and tools

Headquarters: Redmond, WA, USA
Founded: 1975
Company Size: 220,000+ employees
Key Products: Microsoft Copilot, Copilot for Microsoft 365, Microsoft Copilot Studio, Microsoft Copilot in Bing
Market Cap: $3.01 trillion

Microsoft is one of the most dynamic leaders in generative AI today, developing many of its own generative AI tools while supporting and funding new technologies from OpenAI. Bing, the Microsoft-owned search engine, was the first major search engine to incorporate generative AI functions via chatbot, and Microsoft’s family of Copilot technologies is one of the most far-reaching generative AI assistants on the market today.
Copilot is deeply integrated in many of Microsoft’s most popular business and enterprise tools, which are already some of the most popular business applications in use today. These are the main instances of Copilot that are available for enterprise and workplace assistance tasks:

Microsoft Copilot: The casual chat interface that supports text and voice inputs, document attachments, and multimodal outputs through various GPTs.
Copilot for Microsoft 365: Assistive content generation in Microsoft 365 apps, like Word and Excel, but also in more complex business tools, like Dynamics 365 and Power BI.
Copilot for Sales: This sales-focused solution works in both Dynamics 365 and Salesforce.
Copilot Studio: With this solution, users can customize existing Microsoft Copilot tools or build their own custom solutions.
GitHub Copilot: GitHub, which is owned by Microsoft, has its own copilot solution that assists with coding and other developer tasks.

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Pros and cons

Pros
Cons

Smooth generative AI integration with Microsoft products.
Expensive solutions, especially for larger teams.

Partnership with OpenAI.
Limited usability outside of Microsoft-owned products.

Pricing
Like OpenAI, Microsoft offers multiple generative AI solutions that are all priced differently; in some cases, you purchase the generative AI tool directly, while in others, it is available as part of an existing Microsoft tool subscription. We’ll cover pricing information for some of the most popular solutions in the Microsoft tool stack below:

Microsoft Copilot: Free for baseline version; $20 per month for Microsoft Copilot Pro.
Copilot for Microsoft 365: $30 per user per month, plus a Business Standard or Business Premium Microsoft 365 license.
Microsoft Copilot Studio: $200 for up to 25,000 messages per month.
GitHub Copilot: Free version; paid plans range from $10 to $39 per user per month.
Microsoft Copilot for Sales: $50 per user per month.

Features

Close partnership and collaboration with OpenAI.
Copilot access in Microsoft 365 apps, including Dynamics 365.
Custom copilot building opportunities in Copilot Studio.
Copilot solution in preview for Power BI.
AI-powered browser solutions.

For a full portrait of the AI vendors serving a wide array of business needs, read our in-depth guide: 150+ Top AI Companies 2024.

Alphabet (Google)
Best for online, integrated generative AI solutions

Headquarters: Mountain View, CA, USA
Founded: 1998
Company Size: 180,000+ employees
Key Products: Gemini, Vertex AI, Gemini for Google Workspace
Market Cap: $1.72 trillion

Google has generated extra buzz around its generative AI capabilities over the past few months with its release of Gemini, a collection of generative AI models that combines the strengths of Google’s previous models, LaMDA and PaLM 2, for a scalable and multimodal content experience.
Whether users select the free or paid version of Gemini’s AI chatbot interface, they can submit multimodal inputs, receive multimodal outputs — often with relevant webpages and images included — and benefit from several different quality management and fact-checking features. Additionally, Gemini gives users the ability to turn on relevant Google extensions, ensuring that generated results not only benefit from Google Search information but also from Google Flights, Hotels, Maps, Workspace, and YouTube.
Even with these most recent innovations, the company continues to develop artificial intelligence with scalability and ethics both at the forefront. Its AI Principles were established in 2017 to guide AI development, and Google regularly releases reports about how they’re putting those principles to work in their latest releases and product updates.

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Pros and cons

Pros
Cons

Integration with Google Search and apps.
Image output concerns and issues.

Comprehensive quality management features.
Some issues with logical outputs and query responses.

Pricing

Gemini: Free.
Gemini Advanced: Available through Google One AI Premium subscription, which is $19.99 per month after a two-month free trial.
Business add-on for Google Workspace: Starting at $20 per user per month, billed annually.
Gemini Enterprise for Google Workspace: Starting at $30 per user per month, billed annually.
Gemini 1.0 Pro API: Free through Google AI Studio for up to 60 queries.

Features

AI Principles guiding product research and development.
Gemini 1.0 in three different sizes: Ultra, Pro, and Nano.
Google Search and widgets to support content outputs.
Multimodal inputs and outputs with fact-checking capabilities.
Mobile version for iOS and Android users.

Amazon (AWS)
Best for generative AI as a service

Headquarters: Seattle, WA, USA
Founded: 1994
Company Size: 1.5 million+ employees
Key Products: Amazon Bedrock, Amazon Q, Amazon CodeWhisperer, Amazon SageMaker
Market Cap: $1.79 trillion

AWS not only develops several advanced generative AI solutions but also offers its customers various managed services so they can access existing foundation models, build their own foundation models, and benefit from other generative AI solutions and use cases, depending on business need.
SageMaker is a great solution for users who want to start from scratch, while Bedrock offers managed access and support for users who want to customize third-party models like Anthropic’s Claude, Cohere’s Command and Embed, Stability AI’s Stable Diffusion, and Meta’s Llama 2.
AWS’s customers for generative AI range from small startups to major enterprises and brands like Intuit, Nasdaq, Adidas, and GoDaddy. In addition to its managed services and knowledgeable in-house support specialists, customers can benefit from a diverse partner network and the AWS Marketplace.

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Pros and cons

Pros
Cons

Fully managed generative AI service options.
Complicated pricing approach.

AWS Free Tier for experimentation.
Pricing can quickly get expensive.

Pricing
Pricing for Amazon’s generative AI solutions is highly variable. While most organizations will need SaaS, managed services, usage-based, and other pricing models that can get expensive, it’s important to know that several of these solutions can be used in limited ways through the AWS Free Tier.

Amazon Bedrock: Pricing dependent on provider, model, and selected modality. Learn more about the specifics here.
Amazon SageMaker: Pricing is highly customizable for this product. Learn more here.
Amazon Q: Between $20 and $25 per user per month, depending on selected plan.
Amazon CodeWhisperer: Free individual plan; $19 per user per month for Professional plan.

Features

Access to third-party models through Amazon Bedrock.
Foundation model building via Amazon SageMaker.
PartyRock playground for Amazon Bedrock.
Proof of concept development through Generative AI Innovation Center.
Amazon Q and CodeWhisperer applications for user-experience tasks.

To gain a deeper understanding of the AI app sector, read our guide to Best AI Apps for Mobile.

NVIDIA
Best generative AI infrastructure and hardware provider

Headquarters: Santa Clara, CA, USA
Founded: 1993
Company Size: 29,000+ employees
Key Products: NVIDIA AI, NVIDIA NeMo, NVIDIA BioNeMo, NVIDIA Picasso, various chips and GPUs
Market Cap: $2.14 trillion

NVIDIA is one of the top providers of the hardware necessary to power large-scale generative AI models on the market today. It offers dozens of GPU options that work for different memory configurations, boost clock speed, and other requirements. Additionally, it has further democratized generative AI access with recent hardware and computer releases, including new RTC-powered PCs and workstations.
Although NVIDIA is best known for the hardware and software infrastructure solutions it supplies to the AI market, it also offers several of its own generative AI solutions to users. These include NeMo and BioNeMo, both of which give users a cloud-native framework to develop and deploy generative AI models according to their specifications.

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Pros and cons

Pros
Cons

A leading producer of GPUs and compute resources for generative AI.
Some performance issues with lower-level GPUs.

Frequent innovations in GPU, hardware, and software solutions.
Steep learning curve for NVIDIA products.

Pricing
Through NVIDIA, users can purchase several different types of GPUs and other hardware that can be used for generative AI compute and processing power. The vendor also offers subscriptions to several of its own generative AI tools. We’ve covered pricing for some of the most popular solutions below:

NVIDIA GeForce RTX GPUs: Pricing ranges between $399 and $1,599.
NeMo: Free, open-source access through GitHub; free container access via NVIDIA NGC; pricing information available upon request for NVIDIA AI Enterprise.
NVIDIA LaunchPad: Various free, hands-on labs.
BioNeMo: Free access to BioNeMo Framework Training; Beta application process for Cloud APIs access.

Features

LaunchPad for access to free hands-on lab environments.
Generative-AI-ready laptops and desktops.
Dozens of generative-AI-level GPUs and other hardware solutions.
NeMo, BioNeMo, Picasso, and ACE models and foundries.
DGX and Certified Systems accelerated infrastructure.

Anthropic
Best for generative AI safety and explainability

Headquarters: San Francisco, CA, USA
Founded: 2021
Company Size: 50-300 employees
Key Products: Claude 3, Claude API
Market Cap: Private company valued at $15 billion

Anthropic is a leading generative AI startup that believes quality and safety should take precedence over quantity and speed, though it’s important to note that this vendor offers one of the largest context windows on the scene of generative AI models and chatbots. Its team is made up of AI researchers and engineers but also policy experts, business leaders, and stakeholders from across government, academic, nonprofit, and industrial backgrounds.
Anthropic’s flagship product is Claude, an AI assistant that focuses on high-quality content generation, summarization, and explanations. Claude is highly customizable and can be used for workflow automation, natural language conversation, text processing, and Q&A. Its capabilities and quality have also grown with the recent release of Claude 3.

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Pros and cons

Pros
Cons

Focused on transparent, explainable AI research and development.
Expensive per-token pricing for Claude 3.

Claude balances utility with appropriate/inoffensive responses.
Claude cannot access the internet.

Pricing
The Claude versions listed below are the most popular today. Users can also find legacy model pricing information here.

claude.ai: Free online access.
Build plan: API access appears to be free; this plan offers access to all Claude model versions.
Scale plan: Pricing available upon request; this plan offers access to all Claude model versions.
Claude 3 Haiku: $0.25 per 1 million input tokens and $1.25 per 1 million output tokens.
Claude 3 Sonnet: $3 per 1 million input tokens and $15 per 1 million output tokens.
Claude 3 Opus: $15 per 1 million input tokens and $75 per 1 million output tokens.

Features

Extensive AI research library.
Free, multimodal content generation via claude.ai.
API access for multiple Claude versions.
Three Claude 3 versions: Haiku, Sonnet, and Opus.
200k context window.

Cohere
Best for natural language processing

Headquarters: Toronto, ON, Canada
Founded: 2019
Company Size: 50-300 employees
Key Products: Command, Embed, Chat, Generate, Semantic Search
Market Cap: Private company valued at $2.2 billion

Cohere offers a variety of high-powered natural language processing tools for text retrieval, classification, and generation. Its approach to large language models is comprehensive, not only giving users the ability to generate new content but also to search and summarize large sets of pre-written content. With a user-friendly API, app integrations, and quickstart guides, Cohere makes it possible and encourages companies to customize Cohere products to meet their own requirements.
Cohere’s main models are Command, Embed, and Rerank. These power various capabilities and purpose built solutions: Chat, Summarize, Generate, Embeddings, Semantic Search, and Classify.

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Pros and cons

Pros
Cons

Cohere Playground available for model and parameter testing.
Limited models available for fine-tuning.

Easy-to-use APIs.
Some bugginess and inaccuracies in outputs.

Pricing
Below, we’ve covered pricing information for some of Cohere’s most popular products. You can find additional pricing information here.

Playground: Free, rate limited usage for prototyping and pre-production work.
Chat: Between $0.30 and $0.50 per 1 million input tokens, $0.60 and $1.50 per 1 million output tokens, and $1.00 per million training tokens.
Summarize: $1 per 1 million input tokens and $2 per 1 million output tokens.
Embed: $0.10 per 1 million tokens.
Classify: $0.05 per 1,000 classifications.
Rerank: $1 per 1,000 searches.

Features

Three models: Command, Embed, and Rerank.
Default and fine-tuning models for certain products.
Cohere Playground.
LLM University, Documentation, and Quickstart Guides.
Deployment through Cohere API or Amazon SageMaker.

Glean
Best for workplace search and knowledge management

Headquarters: Palo Alto, CA, USA
Founded: 2019
Company Size: 200-500 employees
Key Products: Glean, Glean Chat, Glean Assistant
Market Cap: Private company valued at $2.2 billion

Glean offers generative AI-powered internal search for workplace apps and ecosystems that meets the needs of both business leaders and employees. Companies across different industries and backgrounds use Glean to make it easier for employees to search for company knowledge and contextualize that information to their roles.
The way Glean is designed, each company has its own dynamic knowledge graph that learns and adapts to specific people, interactions, and content requests. Most recently, the company has also upped its retrieval augmented generation (RAG) approach. Through these innovations, everyone from your engineering team to your sales team can use Glean to find the up-to-date information they need more quickly and easily. Other key features that make this a highly usable tool include:

Verified answers: Save and verify answers to frequently asked questions.
Curated collections: The ability for individual teams to collect and organize documents and links that are most relevant for their team; ideal for onboarding.
GoLinks: Short links that can be created and saved for your most commonly used resources.

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Pros and cons

Pros
Cons

Internal search that balances security and usability.
Little pricing transparency.

Semantic understanding for personalization opportunities.
Some customer support limitations.

Pricing
Pricing information for Glean is available upon request. A demo is also available.
Features

Knowledge graph focused on internal content, people, and communications.
Retrieval augmented generation process.
100+ connectors.
Semantic understanding in personalized searches.
Verified answers and GoLinks.

Jasper
Best for social media and digital marketing content generation

Headquarters: Austin, TX, USA
Founded: 2020
Company Size: 50-200 employees
Key Products: Jasper, Jasper API, Jasper AI Copilot
Market Cap: Private company valued at $1.2 billion

Jasper is a leading generative AI writing tool, and is a favorite for marketers and content creators. It offers features to support blog and email writing, SEO optimization, and art and ad imagery creation. It’s easy to use and access, with both Chrome and Microsoft Edge extensions and the Jasper API.
Jasper has always had a business bent with its focus on marketer-style content, but in February 2023, the company took it to a new level with its announcement of Jasper for Business, which increased its customizable brand voice features and tools.
Its next biggest innovation came in the form of Jasper AI Copilot, which offers more hands-on support for AI-generated content, company knowledge management, and data analytics and insights. Most recently, Jasper has also increased its multimodality and generative AI image generation capabilities through the acquisition of Clipdrop.

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Pros and cons

Pros
Cons

Customizable templates and prompts for branding.
Limited features in lower-tier plans.

Easy-to-use browser extensions.
Pricey compared to similar tools.

Pricing

Creator: $39 per user per month, billed annually, or $49 per user billed monthly.
Pro: $59 per user per month, billed annually, or $69 per user billed monthly.
Business: Pricing information available upon request.

Features

50+ AI templates.
Jasper AI Copilot.
Jasper Everywhere browser extensions.
Brand voice library and management.
Accessible, branded chat interface.

Hugging Face
Best for community-driven generative AI development

Headquarters: Brooklyn, NY, USA
Founded: 2016
Company Size: 100-300 employees
Key Products: BLOOM, AutoTrain, Inference Endpoints
Market Cap: Private company valued at $4.5 billion

Hugging Face is a community-driven developer forum for AI and machine learning model development initiatives. Its wide variety of prediction models and datasets makes it possible for organizations to custom-build their own generative AI solutions and other AI toolsets.
Many major enterprises and generative AI startups work on Hugging Face to optimize existing AI models and develop new ones from scratch. Although the forum is designed with developers and programmers in mind, certain Hugging Face solutions, like AutoTrain, require little to no coding. Others, like BLOOM, also offer different levels of accessibility as well as the ability to generate content in a variety of human and computer languages. While quality is questionable on some of the rarer languages included, it has some of the widest multilingual coverage on the market today.

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Pros and cons

Pros
Cons

Open-source, collaborative development environment.
Less friendly to non-technical users.

Embeddable generative AI technology for affordable scalability.
Limited governance over third-party development tools, like Stable Diffusion.

Pricing

Hugging Face Hub: Free.
Pro Account: $9 per month.
Enterprise Hub: Starting at $20 per user per month.
Spaces Hardware: Starting at $0.05 per hour.
Inference Endpoints: Starting at $0.06 per hour.

Features

Community-driven support and resources.
BLOOM for multilingual content generation: 46 languages and 13 programming languages.
Access to most LLMs.
Text generation and logical text completion.
Learned subword tokenizer.

Inflection AI
Best for conversational AI technology

Headquarters: Palo Alto, CA, USA
Founded: 2022
Company Size: Less than 100 employees
Key Products: Pi, Conversational API, Inflection-2.5
Market Cap: Private company valued at $4 billion

Inflection AI earned a formidable reputation long before it released any products simply due to the pedigree of its founders: Mustafa Suleyman, a co-founder of DeepMind and former VP of AI products and AI policy at Google; REid Hoffman, a co-founder of LinkedIn and former EVP at PayPal; and Karén Simonyan, former principal scientist at DeepMind. Unlike many of the other players in this list, Inflection AI is more focused on narrow, purpose-built generative AI solutions rather than AGI. This is evident through Pi, its “personal AI” that focuses on empathetic, conversational AI with humans.
Though Pi is still more focused on conversational AI and personal usage, the recent release of Inflection-2.5 has increased its capabilities for more technical queries and can now provide results based on real-time web searches.
While testing out these new features, I received comprehensive and accurate responses for the most part. However, when I asked Pi how its performance compares against Google’s Gemini, it told me it didn’t know of a Google product by that name. Expect to see more improvements as this new addition to the tool was only released very recently.

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Pros and cons

Pros
Cons

User-friendly mobile access.
No multimodal outputs beyond text and voice.

Founded by former leaders from DeepMind, Google, and LinkedIn.
Some knowledge limitations, though Pi can now access the web.

Pricing
Pi is free to use.
Features

Pi app on iOS and Android devices.
Pi available through WhatsApp, Instagram, Telegram, and Facebook.
Focused R&D on advanced applied AI over artificial general intelligence (AGI).
Inflection-2.5 in-house model.
pi.ai online version.

Adobe
Best generative AI creative suite

Headquarters: San Jose, CA, USA
Founded: 1982
Company Size: 29,000+ employees
Key Products: Adobe Sensei, Adobe Firefly, AI Assistant
Market Cap: $253.62 billion

Adobe has long been the leader for creative software suites, offering tools that support graphic design, video creation, photo editing, and other creative tasks for personal and business projects. Adobe has jumped into generative AI in a significant way, offering generative AI capabilities directly to its users in both the Creative Cloud and Experience Cloud, meaning users can benefit from generative AI assistance and capabilities while creating marketing content and while managing customer experiences.
Adobe’s main generative AI solutions at this time are Sensei and Firefly. Sensei primarily works in Experience Cloud, helping users with AI-powered forecasting and analytics, asset intelligence, personalized commerce experiences, customer journey management and automation, and more. Adobe Firefly is offered through Creative Cloud, giving users the ability to generate images with text prompts, fill and recolor images, and create text effects. Depending on the tool you’re using, Adobe’s generative AI can also support quick content summarization tasks.

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Pros and cons

Pros
Cons

Deep AI integration with Adobe Creative Cloud and Adobe Experience Cloud.
Some limitations on generative credits in Creative Cloud plans.

Innovative research in image and multimedia editing.
Occasional inaccuracies in generated images; missing key prompt details.

Pricing

Adobe Sensei: Sensei is included with each Adobe Experience Cloud product. You can find pricing for these products here.
Adobe Firefly: Limited, free version.
Adobe Firefly Premium Plan: Starting at $4.99 per month.
Adobe Express Premium Plan: Starting at $9.99 per month.
Adobe Creative Cloud: Generative credits and add-ons are available for several Adobe Creative Cloud products. You can find more specific pricing information here.

Features

Adobe Sensei for marketing workflow, customer journey, and analytics support.
Adobe Firefly for AI-powered image and photo generation and effects.
Content Authenticity INitiative and Coalition for Content Provenance and Authenticity.
Adobe Acrobat Assistant and Generative Summary in beta.
Personal and business use access to generative credits.

IBM
Best for AI and data governance

Headquarters: Armonk, NY, USA
Founded: 1911
Company Size: 280,000+ employees
Key Products: watsonx.ai, Code Assistant, Slate, Granite
Market Cap: $175.77 billion

IBM is an established tech enterprise in virtually all categories, now including generative AI. Its Watsonx family of generative AI assistive tools and features is an asset for both data and AI model lifecycle management, as each version of the watsonx tool focuses on a key area of AI development: AI governance, data management, and orchestration, for example.
With Watsonx.governance, users can monitor and govern IBM generative AI models as well as models in third-party platforms like Amazon Bedrock, OpenAI’s platforms, and Microsoft Azure. Compliance, risk management, and lifecycle governance are core parts of this framework, which includes a focus on driving AI explainability through detailed model factsheets.

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Pros and cons

Pros
Cons

Extensive AI and data governance assistance through watsonx.
Steep learning curve for some users.

Helpful CEO guides for how to use generative AI.
Complex pricing structure with limited transparency.

Pricing
Pricing for IBM Watsonx products is available through SaaS tiers and individual software solution pricing. We’ve covered the basics below, but you can find more pricing information here.

SaaS Essentials: $0 per month plus per-hour node and services access and $0.60 per resource unit used in watsonx.governance.
SaaS Standard: $1,050 per month plus per-hour node and services access; no watsonx.governance is available for this plan at this time.
watsonx Assistant: $0 for Lite, starting at $140 per month for Plus, and custom pricing for Enterprise.
Per-product pricing: Varies.

Features

Watsonx.ai for content generation, classification, summarization, extractions, and Q&A modeling.
Watsonx.data for AI and data workload management.
Watsonx.governance AI workflow and development management with transparency and explainability focus.
Watsonx Assistant for real-time customer assistance tasks.
Watsonx Code Assistant for code generation assistance.

C3.ai
Best for enterprise generative AI application development

Headquarters: Redwood City, CA, USA
Founded: 2009
Company Size: 500-2,000 employees
Key Products: C3 AI Platform, C3 Generative AI, C3 AI Pilot
Market Cap: $3.77 billion

C3.ai is a leading solutions provider for enterprise generative AI, offering prebuilt solutions and tools to custom-build LLM-agnostic, enterprise AI applications in major cloud ecosystems. Though virtually any business could partner with C3.ai to develop an application that addresses their business’s pain points, C3.ai focuses primarily in manufacturing, utilities, oil and gas, financial services, government, defense and intelligence, healthcare, retail, transportation, and telecommunications.
The company offers prebuilt suites of tools for various industries and business use cases, including CRM, reliability, sustainability, supply chain, and financial services management. For any solutions you need that aren’t already covered, you can use the C3 AI Platform to build and C3 AI Pilot to support a streamlined app deployment process in approximately six months.

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Pros and cons

Pros
Cons

App development and tools for specific enterprise use cases.
Some volatility in market cap and valuation over time.

Strong industry and manufacturing experience.
High upfront investment costs.

Pricing
Generally speaking, C3 Generative AI application development and licensing costs $250,000 for 12 weeks of production plus additional costs per vCPU or vGPU used per hour after that point. Pricing may also depend on which cloud you purchase from:

C3 Generative AI in Google Cloud: $83,333.33 per month; no usage fee charged here.
C3 Generative AI: Production Pilot in AWS: $250,000 for three months.
C3 Generative AI: Production Pilot in Microsoft Azure: $250,000 for three months plus on-demand $0.55 per vCPU or vGPU hour.

Features

C3 AI Pilot.
C3 AI Platform available via AWS, Azure, and Google Cloud.
Search and chat interface for enterprise knowledge management.
Industry-specific and business-process-specific versions of C3 Generative AI.
C3 Generative AI designed specifically for Databricks, Dynamics 365, Oracle ERP, Oracle Netsuite, Palantir, Salesforce, SAP, ServiceNow, Snowflake, and Workday.

Meta
Best for generative AI cybersecurity

Headquarters: Menlo Park, CA, USA
Founded: 2004
Company Size: 67,000+ employees
Key Products: Meta AI, Llama 2, Llama 3 (coming soon), Seamless Communication models
Market Cap: $1.23 trillion

Meta, the parent company of Facebook, has forged a creative path forward in the generative AI landscape, focusing first and foremost on ethical AI development and developing free, open-source models that can work on consumer-grade hardware without major performance issues. In recent months, it has expanded its focus to Meta AI, an AI assistant and solution that works directly in Meta apps like Facebook, Instagram, and WhatsApp to support image generation and other creative content tasks.
But where Meta really shines is in its commitment to privacy and security. At the end of 2023, the company announced Purple Llama, a project with open trust and safety tools, the company’s Responsible Use Guide, and CyberSec Eval, which includes detailed cybersecurity safety evaluation benchmarks for generative AI models. The company has also released Llama Guard, a safety classifier that controls input and output quality without impacting deployment or performance.

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Pros and cons

Pros
Cons

Access to free, consumer-grade, open-source solutions.
Some model parameter and performance limitations.

Purple Llama for increased generative AI security.
Learning curve for open-source models.

Pricing
Most generative AI solutions from Meta are free and open source.
Features

AI Research and AI Resources libraries.
Purple Llama for developer-driven security.
Llama open platform for AI modeling.
Meta AI image generation with responsible AI labeling.
Meta AI messaging in Instagram, Facebook Messenger, and WhatsApp.

Databricks
Best for large-scale data preparation for AI projects

Headquarters: San Francisco, CA, USA
Founded: 2013
Company Size: 1,000-3,000 employees
Key Products: Mosaic AI, Data Intelligence Platform, Unity Catalog, Vector Search, Data Lakehouse Platform
Market Cap: Private company valued at $43 billion

Databricks is one of the fastest-growing tech companies in the world today, and while its focus is on big data and the full lifecycle of data management, this specialization naturally has led to innovations in generative AI.
Through Mosaic AI, which is built on the Data Intelligence Platform, users can build LLMs and predictive models alike in an environment where they own and have complete control over the data going into these models. Users can build models in Mosaic AI through prompt engineering, retrieval augmented generation (RAG), fine-tuning an existing mo